加工面点云数据深度学习的加工特征自动识别

加工特征识别是实现CAD/CAPP/CAM系统集成的关键技术.针对传统基于符号推理加工特征识别模式存在鲁棒性问题,提出一种基于加工面点云数据深度学习的加工特征自动识别方法;基于PointNet点云识别框架,构建了一个面向加工面点云数据的加工特征自动识别卷积神经网络;通过收集CAD模型中的加工特征面集和采样点云,构建了适...

Automatic Recognition of Machining Features Based on Deep Learning of Machining Surface Point Cloud Data

Machining feature recognition is the key technology to realize the integration of CAD/CAPP/CAM. To tackle the robustness problem of the traditional recognition pattern of machining features based on symbolic reasoning, this study proposes an automatic recognition method of machining features based on deep learning of machining surface point cloud data. Utilizing the PointNet point cloud recognition framework, the study constructs a convolutional neural network (CNN) for automatic recognition of machining features of machining surface point cloud data. By the collection of the machining surface sets from CAD models and sampling of them to form point cloud data, a three-dimensional point cloud data library is constructed which is suitable for the learning of the network framework. A recognizer of machining features can be obtained by the CNN network training, able to automatically recognize 24 kinds of machining features, with the accuracy being higher than 99%. The method is simple, efficient, and insensitive to the point cloud data with noise and defects. Furthermore, it has good robustness and recognition effect for the damage of machining surfaces caused by feature intersection.